Algebraic Feature Extraction of Images for Recognition
用于图象识别的图象代数特征抽取

In this paper, it is proved that the Singular Value (SV) feature vector has some important properties such as the invariance to the algebraic and geometric transformations, and the insensitiveness to noise, Therefore, th SV feature is very useful for describing and recognizing images. As an example, the SV feature vector is used to a problem of recognizing human facial images. The normal pattern Bayes classification model based on the Sammon optimal discriminant plane is constructed. The experimental results show that the SV feature vector has strong ability for the separating classes.